From Qubits to Cures: The Promise of Quantum Computing in Pharmaceutical Research and Development (a Realistic View)

by Andrii Buvailo, PhD          Biopharma insight

Disclaimer: All opinions expressed by Contributors are their own and do not represent those of their employers, or BiopharmaTrend.com.
Contributors are fully responsible for assuring they own any required copyright for any content they submit to BiopharmaTrend.com. This website and its owners shall not be liable for neither information and content submitted for publication by Contributors, nor its accuracy.

   1617    Comments 0
Topics: Emerging Technologies   
Share:   Share in LinkedIn  Share in Reddit  Share in X  Share in Hacker News  Share in Facebook  Send by email   |  

In a recent announcement, Moderna and IBM unveiled their partnership aimed at utilizing cutting-edge technologies, such as artificial intelligence (AI) and quantum computing, to accelerate research in messenger RNA (mRNA) therapeutics and vaccines. This collaboration highlights the growing interest in the potential of quantum computing within the life sciences sector.

Quantum computing, a branch of computer science, focuses on leveraging the principles of quantum theory to solve complex problems that classical computers are unable to address. The partnership between Moderna and IBM will explore various use cases of quantum computing within the life sciences, particularly mRNA medicine design.

As part of the collaboration, both organizations will employ MoLFormer, an AI-based foundation model, to predict the properties of molecules and gain insights into the characteristics of potential mRNA medicines. Moderna plans to utilize MoLFormer to optimize lipid nanoparticles in mRNA, which protect it as it travels within the body, and the mRNA itself, responsible for instructing cells on combating diseases. By incorporating AI and formulation discovery approaches, Moderna aims to create advanced mRNA medicines.

During the collaboration, Moderna will participate in the IBM Quantum Accelerator program and the IBM Quantum Network. IBM, in turn, will offer access to and expertise in quantum computing systems and their applications within the life sciences industry.

IBM's plans for universal quantum computing in the medical field, unveiled in 2017, have garnered interest among healthcare and life sciences organizations. However, concerns regarding the technology's impact on healthcare data security remain. In October 2022, Cleveland Clinic announced its partnership with IBM to install the first healthcare quantum computer in the US, called the IBM Quantum System One. This installation is part of the Cleveland Clinic's initiative to accelerate biomedical discoveries and the Cleveland Clinic-IBM Discovery Accelerator, a 10-year collaboration to advance biomedical research.

The partnership between Moderna and IBM marks a significant step in exploring the potential of quantum computing and AI for drug discovery and the development of mRNA therapeutics. With more organizations recognizing the advantages these technologies can bring, the life sciences industry may see substantial advancements in the coming years.

 

What can quantum computers do?

Quantum computing operates by substituting classical computing's bits with quantum bits, commonly referred to as "qubits." Unlike bits, which can only store binary values of 0 or 1, qubits can exist as a superposition of both 0 and 1 simultaneously. This is made possible through a phenomenon in quantum mechanics called entanglement.

Theoretically, quantum computers can evaluate all potential states or results of a problem and analyze them concurrently, says Robert Penman, an analyst at GlobalData, the parent company of Clinical Trials Arena. However, constructing a functional quantum computer is a complex and resource-demanding task.

One of the main challenges is maintaining the stability of individual qubits long enough to perform a calculation. Most quantum computing systems being developed rely on atoms or ions, which must be cooled to extremely low temperatures in a laboratory environment. Additionally, scaling quantum computers presents a significant hurdle, as increasing the number of qubits in a system raises the possibility of erroneous signaling, according to Penman.

Nevertheless, small-scale quantum computers may offer added value in the short term while the development of large-scale commercial systems continues. Some of the companies are pioneering applied quantum computing for drug discovery. One of the vivid examples of applying quantum computing already today is Durham-based POLARISqb, founded in 2020. 

 

Applied quantum computing for discovering chemical modalities

POLARISqb has been employing the extraordinary processing capabilities of quantum computing to identify optimal lead compounds for drug development more efficiently and cost-effectively than traditional methods.

Computer-aided drug design (CADD) has long been a valuable tool in the pharmaceutical industry, as it enables researchers to predict the biological activity of potential drug-like molecules before conducting lab experiments. However, conventional CADD systems are limited in scope, only able to explore a relatively small pool of compounds. POLARISqb aims to overcome this limitation by expanding the chemical space, transforming drug design into an optimization problem that can be solved in a single step.

Co-founders Shahar Keinan and Bill Shipman have been pursuing this goal since they established the company in 2020. Their quantum-inspired technology allows for the efficient scanning of large chemical spaces for potential drug candidates at unparalleled speeds. POLARISqb has developed the first drug discovery platform that utilizes a quantum annealer, a type of quantum computer designed to tackle complex combinatorial optimization problems. This quantum annealer can swiftly solve problems that are otherwise too complex for classical computers.

Instead of calculating all possibilities through a brute-force approach, a quantum system's wave function scans them to identify the best molecule among billions in a single pass. POLARISqb specializes in converting chemistry into the language of quantum computers, creating chemical spaces in the format of quadratic unconstrained binary optimization (QUBO) algorithms that run on a quantum annealer for optimization.

POLARISqb has demonstrated the validity of its approach with over 15 drug discovery projects and a promising portfolio of lead molecules. The company's computational chemists have identified drug candidates targeting the RNA-dependent RNA polymerase of the Dengue virus, a mosquito-borne disease with no current cure, affecting up to 40% of the global population. The team built a chemical library of 1.3 billion compounds and used a quantum annealer to assess the library and design molecular leads. Within six months, they were able to prioritize molecules for experimental testing. Out of 30 final lead molecules, 10 shared similar motifs with molecules identified by Novartis after seven years of research.

Collaborating with several companies, POLARISqb seeks to integrate quantum technologies and advanced artificial intelligence (AI) to discover novel lead compounds for a wide range of medical indications. One such partnership is with Auransa, where they combine their expertise in AI-driven biology and quantum-computing-based chemistry to find therapeutics for diseases disproportionately affecting women. Together, they are searching for and testing molecules targeting a dysregulated pathway in triple-negative breast tumors.

In June 2023, POLARISqb plans to offer a Software-as-a-Service (SaaS) platform called QuADD, executed on a quantum annealing system. Clients can submit their target and small-molecule requirements to the QuADD platform, which scans large chemical spaces while maintaining data confidentiality. QuADD identifies the top enriched library of candidates from billions of molecules in just a few days, allowing customers to speed up the hit-to-lead process.

QuADD has already proven successful in reverse-engineering known drugs, such as the commercial oncology drug Nexavar (sorafenib). Keinan believes that QuADD is among the first SaaS quantum-based products on the global market and the only one for drug design. By utilizing QuADD to create novel, enriched molecular libraries of lead molecules, POLARISqb aims to close the discovery gap in the search for new lead molecules.

 

Pioneers of quantum computing for drug discovery

POLARISqb is not alone in its efforts to bring the practical value of quantum computing to the realm of pharmaceutical research. For example, Qubit Pharmaceuticals, a company with locations in Paris, France, and Boston, MA, is making strides in the field of quantum physics-based drug discovery. The firm's proprietary Atlas software platform harnesses the computing power of supercomputers and quantum computers to expedite the development of safer and more effective drug candidates. Qubit Pharmaceuticals recently secured €16 million in funding, with backers such as XAnge, Omnes, Quantonation, and Octave Klaba.

The Atlas platform allows Qubit Pharmaceuticals to accurately model quantum effects at the microscopic level, simulating the interactions between molecules with exceptional precision. By creating digital twins of physical molecules, Atlas performs calculations in a few hours that would conventionally take several years, accelerating the process by a factor of 100,000. This eliminates the need to synthesize drug candidates developed in chemistry or using artificial intelligence algorithms for effectiveness validation. Atlas enables the modeling, description, and prediction of molecules and their actions.

With this technology, Qubit Pharmaceuticals addresses three key challenges in drug development: prediction quality, result interpretability, and simulation speed. Under the leadership of CEO Robert Marino and Chief Scientific Officer Jean Philip Piquemal, Qubit Pharmaceuticals has already formed long-term partnerships with organizations that are developing high-performance computing infrastructures, such as Nvidia, GENCI, and AWS, as well as those focused on quantum computing, including France's Pasqal and the University of Sherbrooke in Canada.

Another example, Zapata Computing, a Boston-based quantum software company, provides industrial and commercial computing solutions for various use cases, including pharmaceutical research. Established in 2017, the company has its roots in Alán Aspuru-Guzik's laboratory at Harvard, where he worked on developing quantum computing methods for chemical simulations. To date, Zapata has raised $67.4 million from multiple investors, such as Prelude Ventures and Comcast Ventures. The company's research platform, "Orquestra," combines a robust software platform with quantum algorithm libraries tailored for applications in chemistry, biopharma, machine learning, and optimization. 

Finally, there is Riverlane, a UK-based company headquartered in Cambridge, which claims to be "the world's first quantum engineering company." Established in 2017, Riverlane has raised a total of $42.8 million to develop its quantum hardware and software technologies for a diverse array of applications, encompassing pharmaceutical research and chemistry.

In July 2021, Riverlane collaborated with Rigetti Computing and joined forces with existing partner Astex Pharmaceuticals to propel quantum computing advancements in drug discovery.

One of Riverlane's significant projects is Deltaflow.OS®, an operating system designed for quantum computers. This groundbreaking operating system addresses one of the critical bottlenecks in today's quantum computing landscape: quantum error correction.

 

The afterthought: the convergence of artificial intelligence and quantum computing

In an interview for BiopharmaTrend, Christopher Savoie, CEO of Zapata Computing, discussed the convergence of artificial intelligence (AI), specifically machine learning and deep learning, and quantum technology in the pharmaceutical industry. He emphasized that quantum technology will be a key enabler for accelerating progress in AI. Savoie believes that even relatively small, noisy quantum computers can enhance AI applications, and he sees this as a software problem with quantum components. Zapata is not just focused on quantum software but also classical software, as they are part of the data science and machine learning business. Savoie envisions quantum technology becoming an integral part of nearly every data science and machine learning workflow in biopharma. The adoption of quantum tech will enable more accurate models, driving the industry to incorporate it into their processes.

 

Topics: Emerging Technologies   

Share:   Share in LinkedIn  Share in Reddit  Share in X  Share in Hacker News  Share in Facebook  Send by email

Comments:

There are no comments yet. You can be the first.

Leave a Reply

Your email address will not be published. Required fields are marked *